Modern businesses will have to deal with customer data in one way or another. The COVID-19 pandemic has proven that the only businesses that will survive in the future are those willing to embrace technology. While technologies such as IoT and AI have undeniable advantages, they also bring complexity.
Managing the data of your customers or website visitors is a lot like being close to their home. If businesses fail to prioritize data privacy and security in the early build stages of their business, it could come back to haunt them at the most inconvenient moment. Hence, the importance of privacy-enhancing technologies (PET) is increasing.
This guide will explore what privacy-enhancing technologies are and how your company can benefit from using them.
What are privacy-enhancing technologies?
Privacy-enhancing technology or PET is designed to prevent data leakage while balancing privacy with usability. Some PETs even prevent bad actors from identifying who the collected data belongs to — data that would be of little use to cybercriminals in the event of a leak.
Other PETs avoid costly data breaches through cryptographic protection during data processing. PET can also come in the form of a remote auditing service to monitor and ensure that data is only being processed for the correct purpose. This minimizes the chances of data leakage and breaches.
Your company may have all the necessary data and know everything about it, but building an online and software-based service that is private by design is challenging. PET can help you launch privacy-preserving services to prevent catastrophic data breaches.
Types of Privacy-Enhancing Technologies
In fact, the term “privacy-enhancing technology” is a bit vague. It refers to any technology that represents an essential element of data protection. Therefore, any tool that can minimize personal data usage while maximizing data security falls into this category. Types of PET include:
Traffic analysis is one of the biggest threats to data security and privacy. Bad actors shouldn’t be able to monitor your online footprint or communications. You can prevent this intrusion by encrypting your communications with a reputable VPN provider when you are connected to a public network. This is one of the easiest yet most effective strategies you can use to hide your online footprint. A good VPN hides your browsing history, personal data, login information, and IP address, making it harder to be tracked while you’re online.
Pseudonymization and obfuscation are other forms of data masking. This is where sensitive data is distorted, masked, or replaced with fake data. Companies can even leverage machine learning algorithms to create synthetic data.
Businesses can also protect their customers by minimizing the amount of personal data they collect. This is called data minimization.
Encryption tools are the oldest form of PET. For example, we’ve seen how uniquely derived encryption per field can effectively protect crypto assets with crypto wallets.
Homomorphic encryption is a good example of modern cryptographic methods used in data privacy. The process involves encoding the data so that operations can still be performed on the data without decrypting it. This is similar to how you would open a zip folder and change the files in it.
There are two main types of homomorphic encryption (some sources cite three):
- Fully Homomorphic Encryption (FHE)
- Partially Homomorphic Encryption (PHE)
Secure Multi-Party Computation (SMPC) is another form of encryption used in PET. In this approach, a portion of the data is encrypted by multiple parties, similar to how P2P swarm systems work.
Differential privacy in data cryptography is functionally similar to obfuscation. The data is masked by a layer of statistical noise. This method is often used in statistics because it hides data related to individuals while still showing data that allows you to identify patterns related to groups.
Finally, zero-knowledge proofs (ZKPs) work like homomorphic encryption, where data can be used without being compromised. ZKP allows you to verify data (or use it for verification) without decrypting it.
How to choose a pet?
There are many impressive privacy-enhancing tools on the market. However, it’s important to determine how they fit into your software stack and IT infrastructure. Therefore, you must recognize the specific data privacy needs of your service and business. you should:
- Determine the volume and type of data your business handles. Are most of them structured or unstructured?
- Identify third-party services, if any, with which you share data. If your data is passed between third parties, then homomorphic encryption is your best option.
- Distinguish which parts of the data you need. For example, do you need full access to the dataset or just the results/outputs? Can you deny sensitive data (personally identifiable information) that can be used to identify an individual?
- Determine the purpose of the data. Will it be used for statistics, market data or training machine learning models, and other similar purposes?
- Assess your IT infrastructure and your network and computing capabilities. This will help you determine whether a particular PET is compatible with your business’ resources. Additionally, you can use this information to determine which parts of your IT infrastructure need to be upgraded.
- Make the necessary preparations in your budget as PET can be expensive – some more expensive than others.
There are many different types of PET, each designed to solve a specific business problem. While some are better at aggregate analysis, others are better at precise results. Again, some may be ideal for gaining insight from sensitive data, while others are best suited for data exploration.
Organizations from different industries are collecting and analyzing all forms of data at an unprecedented rate. Therefore, they must ensure that the data is collected securely while the data is clearly analyzed. This is critical to your business’ public image and financial future. PET should serve as a small part of a larger zero trust solution. When considering cybersecurity and data privacy, it’s important to avoid shortsightedness.
About the author: Gary Stevens is an IT specialist and a part-time Ethereum developer working on open source projects for QTUM and Loopring.He is also a part-time blogger Australian Privacywhere he discusses online safety and privacy.
Editor’s Note: The views expressed in this guest author article are those of the contributor and do not necessarily reflect the views of Tripwire, Inc.